Ethanol/water pulp enzymatic pretreatment: Chemical and FTIR-PCA analyses

Pulps obtained from ethanol/water cooking of sugarcane bagasse were treated at different times using xylanase enzyme obtained from Thermomyces lanuginosus IOC-4145 or commercially (Cartazyme HS, Sandoz Products Ltd.). The enzyme dosage was 18 IU per g of dry pulp and the time varied from 4 h to 12 h. When xylanase from T. lanuginosus was used, the kappa number and viscosity improved independently of the processing time used (4 h, 8 h, and 12 h). After chemical evaluation, the obtained pulps were classified using Fourier Transformed Infra-Red Spectroscopy and Principal Component Analysis. The results showed that the first three principal components explained more than 90 % of the total variance of the pulp spectra.     

主成份分析-偏最小二乘法分光光度法同时测定钴、镍、铜、锌四组份体系

用 PCA 及 PLS 分步处理分光光度数据,有效降低了计算的维数。以该法对不同酸度体系的5-Br-PADAP-钴、镍、铜、锌分光光度数据进行了处理,定量分析结果良好。     

Molecular speciation of microparticles: application of pattern recognition techniques to laser microprobe mass spectrometric data

Attempts were made to enhance the ability of laser microprobe mass spectrometry (LAMMS) to identify molecular species in individual microparticles by applying pattern recognition methods. Principal component analysis (PCA) and canonical discriminant analysis were applied to LAMMS data for nickel-containing environmental particles. Detailed comparison of the two statistical methods demonstrated the utility of PCA. The successful application was highly dependent on the use of appropriate spectral normalization and feature extraction techniques prior to PCA. Although the test system involved only a small number of standard compounds, the LAMMS data were complicated by the effects of intra-particle heterogeneity common to environmental samples and by instrumental limitations. Pattern recognition techniques provided more accurate quantitative assignments of molecular species than were available by qualitative inspection of characteristic cluster ions or by simple spectral subtraction to compare particle data with a library of standard compounds. Results were substantiated by comparison with bulk analysis studies using wet chemical techniques.     

Microstructural model for prediction of stress–strain curves of amorphous and semicrystalline elastomers

A fundamental microstructural model was developed to calculate the stress–strain curves of rubbery amorphous polymers and of semicrystalline polymers with a rubbery amorphous phase by numerical simulations. The rubbery amorphous phase was treated by using a version of the theory of rubber elasticity with finite extensibility. Physical entanglements and chemical crosslinks were both allowed. Slippage was implemented by a Monte Carlo algorithm controlled by kinetic parameters such as the activation energy and activation volume for slippage. The crystalline phase was treated in a very idealized manner, including a crude representation of tie chains but not taking the internal structure of the crystallites into account. A two-dimensional embodiment of the model was implemented into software. For amorphous polymers, while lacking truly quantitative accuracy, the model showed sufficiently good agreement with the experimental trends to be used as a qualitative or semiquantitative predictive tool, and it is currently being used in this manner. The more complex semicrystalline version was less accurate and will need to be improved in future work. Most of the limitations of the semicrystalline version could be ascribed unambiguously to specific simplifications made in the software implementation to reduce the amount of computer time required for the calculations. © 1997 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 35: 2715–2739, 1997     

Einfluß der Sensor-Zeitkonstanten auf die Auswertbarkeit von Ta-Daten

All temperature sensors have a finitely time constant. The influence of the sensor time constant gt_s on the results of kinetic evaluation is demonstrated at four reaction types. The ignorance of the sensor indolence gives incorrect activation parameters. Therefore the determination of _s is necessary.For the estimation of parameters the nonlinear evaluation program TA-kin was used. With its help it is possible to find the real parameters, also when _s=32 s, if the real _s-value was entered.

     

LF-NMR结合化学模式识别鉴别油脂种类及餐饮废弃油脂

应用主成分分析(Principal component analysis,PCA)和聚类分析法(Cluster analysis,CA)对9种(27个)常见食用植物油及100个餐饮废油的低场核磁共振(Low-field nuclear magnetic resonance,LF-NMR)(T2)弛豫特性数据进行分析。结果表明:在正常食用油种类区分方面,主成分分析的效果较优,9种食用油在主成分分布图上按种类正确分组,边界清晰。而在正常食用油与餐饮废油的区分方面,聚类分析效果较优,引入30个待测样本后,聚类分析(127个样品,欧式距离=5)的正确率为94.49%,分析误判率为5.51%,分组效果良好。LF-NMR结合化学模式识别可实现对油脂种类及餐饮废弃油脂的鉴别。     

高效液相色谱法同时测定化妆品中的10种美白活性成分及2种禁用成分

建立了同时测定化妆品中10种美白活性成分及2种禁用成分的高效液相色谱分析方法。水基、乳液等含油脂较少的样品采用0.02 mol/L磷酸二氢钾溶液(pH 6.0)直接提取;油脂含量高的样品及蜡基、粉基类的样品先加入2.5 m L二氯甲烷溶解后再用0.02 mol/L磷酸二氢钾溶液(pH 6.0)提取。提取液在9 500r/min下离心后用0.22μm滤膜过滤。样品采用Eclipse XDB-C_(18)色谱柱为固定相,以0.02 mol/L磷酸二氢钾溶液(pH 6.0)和甲醇溶液为流动相,梯度洗脱,流速为1.0 m L/min,柱温为25℃,使用二极管阵列检测器(DAD)进行检测,检测波长为230 nm和250 nm,外标法定量。结果显示:12种化合物在2.5~100 mg/L范围内线性关系良好,相关系数(r)均大于0.999 0。方法的定量下限(以信噪比为10计)为0.006 5%~0.025%,添加水平为0.025%~0.5%时回收率为87%~102%,相对标准偏差均小于4%。该方法前处理简单、回收率高、精密度好,适用于化妆品中10种美白活性成分及2种禁用成分的快速测定。     

基于内源性致香物质和化学计量学的烟草感官评价研究

采用主成分分析法结合遗传算法和神经网络,建立了基于烟草内源性致香物质的感官质量评价预测模型。利用气相色谱-质谱(GC-MS)技术对超临界萃取-分子蒸馏所得烟草精油中的内源性致香组分进行定性定量分析,汇总各类致香指标后,对其进行主成分分析;以提取所得5个主成分的得分作为输入变量,感官评吸分数作为输出变量,分别使用标准BP神经网络和遗传算法(GA)优化的BP神经网络建立预测模型。对比实验结果表明,GA优化后的模型预测效果更优,其预测值与实验值间的相关系数为0.96,预测均方根误差为1.81,说明GA-BP模型具有更好的拟合能力和预测能力,该模型能有效地预测烟草精油的感官品质。     

一种面向多组分定量的通用谱图解析方法

在一个多组分系统中各组分的定量分析是非常重要的。现代光谱如拉曼光谱(RS)、傅里叶变换红外(FT-IR)光谱、紫外-可见(UV-Vis)光谱、核磁共振(NMR)、质谱(MS)等,可通过获取丰富峰信号的谱图对样品进行各角度的详尽描述。然而,由于谱图的复杂性及其解析工作的繁重,使得仅通过样品谱图来同时量化混合物中的每个组分成为很具挑战性的工作。在这项研究中,我们首次介绍了一个名为定量主成分分析(q PCA)的可靠策略,快速计算混合物中每个成分的比例,而不需要任何手动解谱。通过使用纯组分的谱图作为参考,多组分系统的谱图可以通过PCA自动分辨并解析,然后就可以使用我们的计算方法来计算每个组分的比例。计算机建模实验和RS、FT-IR、UV-Vis、NMR、MS实验都证明了这一策略胜任多组分系统的快速定量工作。     

SpecPad: device‐independent NMR data visualization and processing based on the novel DART programming language and Html5 Web technology

SpecPad is a new device‐independent software program for the visualization and processing of one‐dimensional and two‐dimensional nuclear magnetic resonance (NMR) time domain (FID) and frequency domain (spectrum) data. It is the result of a project to investigate whether the novel programming language DART, in combination with Html5 Web technology, forms a suitable base to write an NMR data evaluation software which runs on modern computing devices such as Android, iOS, and Windows tablets as well as on Windows, Linux, and Mac OS X desktop PCs and notebooks. Another topic of interest is whether this technique also effectively supports the required sophisticated graphical and computational algorithms. SpecPad is device‐independent because DART's compiled executable code is JavaScript and can, therefore, be run by the browsers of PCs and tablets. Because of Html5 browser cache technology, SpecPad may be operated off‐line. Network access is only required during data import or export, e.g. via a Cloud service, or for software updates. A professional and easy to use graphical user interface consistent across all hardware platforms supports touch screen features on mobile devices for zooming and panning and for NMR‐related interactive operations such as phasing, integration, peak picking, or atom assignment. Copyright © 2017 John Wiley & Sons, Ltd.